Infective Endocarditis Following Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
Background: No data exist about the characteristics of infective endocarditis (IE) post-transcatheter aortic valve replacement (TAVR) according to transcatheter valve type. We aimed to determine the incidence, clinical characteristics, and outcomes of patients with IE post-TAVR treated with balloon-expandable valve (BEV) versus self-expanding valve (SEV) systems. Methods: Data from the multicenter Infectious Endocarditis After TAVR International Registry was used to compare IE patients with BEV versus SEV. Results: A total of 245 patients with IE post-TAVR were included (SEV, 47%; BEV, 53%). The timing between TAVR and IE was similar between groups (SEV, 5.5 [1.2–15] months versus BEV, 5.3 [1.7–11.4] months; P =0.89). Enterococcal IE was more frequent in the SEV group (36.5% versus 15.4%; P <0.01), and vegetation location differed according to valve type (stent frame, SEV, 18.6%; BEV, 6.9%; P =0.01; valve leaflet, SEV, 23.9%; BEV, 38.5%; P =0.01). BEV recipients had a higher rate of stroke/systemic embolism (20.0% versus 8.7%, adjusted OR: 2.46, 95% CI: 1.04–5.82, P =0.04). Surgical explant of the transcatheter valve (SEV, 8.7%; BEV, 13.8%; P =0.21), and in-hospital death at the time of IE episode (SEV, 35.6%; BEV, 37.7%; P =0.74) were similar between groups. After a mean follow-up of 13±12 months, 59.1% and 54.6% of the SEV and BEV recipients, respectively, had died ( P =0.66). Conclusions: The characteristics of IE post-TAVR, including microorganism type, vegetation location, and embolic complications but not early or late mortality, differed according to valve type. These results may help to guide the diagnosis and management of IE and inform future research studies in the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".